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As the 2010’s draw to a close, it’s worth taking a look back at the monumental progress that has been made in Deep Learning in this decade.
Tags: deep_learning
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### Summary
* We ran a book dash from 7-21 May 2021, and we would like to capture highlights of all attendees
### What needs to be done?
Please make sure that you share your feedback and expe…
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Hello, I have interfaced to MLJ the following BetaML models: `KMeans, KMedoids, GMM, MissingImputator`.
The MLJ documentation is a bit sparse for unsupervised models, compared to supervised ones, so …
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As a training to start with the machine learning with PHP by using this library, I want to create a simple project that will use the old lotto numbers to predict if a generated random numbers sequence…
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Recently I look for RBM in Keras but with no success so far?
Is there somewhere in Keras?
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For Probabilistic models, the [Quick Start Guide](https://alan-turing-institute.github.io/MLJ.jl/dev/quick_start_guide_to_adding_models/#Predict/Transform-1) says the returned value of `predict` shoul…
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**Submitting author:** @mathpluscode (Yunguan Fu)
**Repository:** https://github.com/DeepRegNet/DeepReg
**Version:** v0.1.0
**Editor:** @Kevin-Mattheus-Moerman
**Reviewers:** @ethanwharris, @lbrea, @z…
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How should the tool be structured?
Continuing discussion from #24.
tsalo updated
4 years ago
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Hey,
I've just found your project and papers - very interesting work! We researching in a similar direction: we use Blender to massively randomize a scene in real-time and use this annotated data f…
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As I turn to define more canned composite models (eg `@stack`, `@continuous`) and with the issues #258, https://github.com/alan-turing-institute/MLJ.jl/issues/412, https://github.com/alan-turing-insti…